7 of 7 Semantic Kernel Jobs in London

into campaign performance and ROI• Build and deploy AI automations leveraging LLMs and AI agent frameworks: Design and implement solutions using cutting-edge technologies like LangChain, AutoGen, CrewAI, Semantic Kernel, LlamaIndex, and similar frameworks to automate tasks, enhance decision-making, and improve campaign performance• Stay ahead of the curve on emerging AI technologies: Continuously research and … real-world marketing challenges• Experience building products and automations leveraging Large Language Models (LLMs) and AI agent frameworks• Familiarity and practical experience with tools like LangChain, AutoGen, CrewAI, Semantic Kernel, LlamaIndex, or similar• Demonstrated ability to identify innovative AI solutions and successfully scale them within an organization• Strong coding skills in Python or similar languages, with More ❯

into campaign performance and ROI• Build and deploy AI automations leveraging LLMs and AI agent frameworks: Design and implement solutions using cutting-edge technologies like LangChain, AutoGen, CrewAI, Semantic Kernel, LlamaIndex, and similar frameworks to automate tasks, enhance decision-making, and improve campaign performance• Stay ahead of the curve on emerging AI technologies: Continuously research and … real-world marketing challenges• Experience building products and automations leveraging Large Language Models (LLMs) and AI agent frameworks• Familiarity and practical experience with tools like LangChain, AutoGen, CrewAI, Semantic Kernel, LlamaIndex, or similar• Demonstrated ability to identify innovative AI solutions and successfully scale them within an organization• Strong coding skills in Python or similar languages, with More ❯

practices across the organisation. Skills we would love you to have: Experience in AI/ML engineering or applied machine learning. Proficiency in Python and ML libraries (e.g. Semantic Kernel, Langchain, agentic frameworks). Experience deploying models using APIs, containers, or cloud-native services. Familiarity with Azure and infrastructure-as-code tools. Strong understanding of data … love you to have: Experience in AI/ML engineering or applied machine learning. Proven experience delivering production-grade AI solutions. Proficiency in Python and ML libraries (e.g. Semantic Kernel, Langchain, agentic frameworks). Experience deploying models using APIs, containers, or cloud-native services. Familiarity with Azure and infrastructure-as-code tools. Strong understanding of data More ❯

architectures and solutions. Resolve technical blockers and objections, collaborating with engineering to share insights and improve products. Maintain deep expertise in AI Foundry & App architecture (Agentic AI framework, Semantic Kernel, Foundry SDK, Responsible AI) and App architecture/cloud native dev (APIs, containerization, microservices, event-driven, Python, Java or .NET). Maintain and grow expertise in … design/modernization and cloud native development (e.g., APIs, containerization, microservices, event-driven, Python, Java, .NET). Expertise in AI & ML models (e.g., Agentic AI framework, AI Foundry, Semantic Kernel, Foundry SDK, Responsible AI, fine-tuning/inferencing, etc.). Proven ability to lead technical engagements (e.g., hackathons, PoCs, MVPs) that drive production-scale outcomes. Microsoft More ❯

Experience with cloud-native applications on Azure and deployment of Python applications on Azure. AI Frameworks and Tools: Familiarity with frameworks and tools such as LangChain, LlamaIndex, CrewAI, Semantic Kernel, Autogen and Agno. An understanding of how Large Language Models (LLMs) work. Data Engineering & Modelling: Understanding of ORM/entity relationships, NoSQL, JSON, XML, SQL and More ❯

to deliver real-world results What We’re Looking For • 5+ years' ML experience with strong Python skills • Experience with NLP, LLMs, and prompt engineering • Familiarity with LangChain, Semantic Kernel, or AutoGen • OCR/document layout modelling experience • Cloud-native deployment experience (AWS, Azure, or GCP) • Strong engineering mindset – writing production-grade, scalable code Bonus Points More ❯

uplift capability. Technical Expertise: Hands-on experience applying Generative AI in real-world business settings. Skills in prompt engineering, RAG, guardrail design, orchestration, and tools like LangGraph or Semantic Kernel. Deep knowledge of ML model development, deployment, and evaluation. Proficiency in Python, PyTorch, TensorFlow, SQL, Spark, and AWS tools like SageMaker and Bedrock. Understanding of scalable data infrastructure More ❯